We investigate the datasets used for evaluation in D-NeRF [1]}, HyperNeRF [2]}, Nerfies [3]}, and NSFF [4]}.
Table REF  shows their statistics.
We evaluate the amount of effective multi-view cues via the proposed EMFs, shown in Figure REF .
We find that existing datasets have large EMF values on both metrics.
For example, the HyperNeRF dataset has an \(\omega \)  as large as \(\raisebox {0.5ex}{\xbox {char}{\XMLaddatt {name}{tildelow}}}200^{\circ }/{s}\) .
To put these numbers in context, a person imaging an object \(3{m}\)  away has to move at \(1[per-mode=symbol]{m}\)  to get an \(\omega = 20^{\circ }/{s}\)  (close to the statistics in the proposed dataset). Some datasets exhibit \(\omega \)  higher than \(120^{\circ }/{s}\) , which is equivalent to a camera motion faster than the Olympic \(100{m}\)  sprint record, without incurring any motion blur.
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